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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2002

Software for Improved Extraction of Data From Tape Storage

A computer program has been written to replace the original software of Racal Storeplex Delta tape recorders, which are still used at Stennis Space Center but have been discontinued by the manufacturer. Whereas the original software could be activated by a command-line interface only, the present software offers the option of a command-line or graphical user interface. The present software also offers the option of batch-file operation (activation by a file that contains command lines for operations performed consecutively). The present software is also more reliable than was the original software: The original software was plagued by several deficiencies that made it difficult to execute, modify, and test. In addition, when using the original software to extract data that had been recorded within specified intervals of time, the resolution with which one could control starting and stopping times was no finer than about a second (or, in some cases, several seconds). In contrast, the present software is capable of controlling playback times to within 1/100 second of times specified by the user, assuming that the tape-recorder clock is accurate to within 1/100 second.

Cheng, Chiu-Fu↗
NASA NTRS2002

Software for Improved Extraction of Data From Tape Storage

A computer program has been written to replace the original software of Racal Storeplex Delta tape recorders, which are still used at Stennis Space Center but have been discontinued by the manufacturer. Whereas the original software could be activated by a command-line interface only, the present software offers the option of a command-line or graphical user interface. The present software also offers the option of batch-file operation (activation by a file that contains command lines for operations performed consecutively). The present software is also more reliable than was the original software: The original software was plagued by several deficiencies that made it difficult to execute, modify, and test. In addition, when using the original software to extract data that had been recorded within specified intervals of time, the resolution with which one could control starting and stopping times was no finer than about a second (or, in some cases, several seconds). In contrast, the present software is capable of controlling playback times to within 1/100 second of times specified by the user, assuming that the tape-recorder clock is accurate to within 1/100 second.

Cheng, Chiu-Fu↗
NASA NTRS2007

Real-Time Data Display

RT-Display is a MATLAB-based data acquisition environment designed to use a variety of commercial off-the-shelf (COTS) hardware to digitize analog signals to a standard data format usable by other post-acquisition data analysis tools. This software presents the acquired data in real time using a variety of signal-processing algorithms. The acquired data is stored in a standard Operator Interactive Signal Processing Software (OISPS) data-formatted file. RT-Display is primarily configured to use the Agilent VXI (or equivalent) data acquisition boards used in such systems as MIDDAS (Multi-channel Integrated Dynamic Data Acquisition System). The software is generalized and deployable in almost any testing environment, without limitations or proprietary configuration for a specific test program or project. With the Agilent hardware configured and in place, users can start the program and, in one step, immediately begin digitizing multiple channels of data. Once the acquisition is completed, data is converted into a common binary format that also can be translated to specific formats used by external analysis software, such as OISPS and PC-Signal (product of AI Signal Research Inc.). RT-Display at the time of this reporting was certified on Agilent hardware capable of acquisition up to 196,608 samples per second. Data signals are presented to the user on-screen simultaneously for 16 channels. Each channel can be viewed individually, with a maximum capability of 160 signal channels (depending on hardware configuration). Current signal presentations include: time data, fast Fourier transforms (FFT), and power spectral density plots (PSD). Additional processing algorithms can be easily incorporated into this environment.

Pedings, Marc↗
NASA NTRS2003

Software for Improved Extraction of Data From Tape Storage

A computer program has been written to replace the original software of Racal Storeplex Delta tape recorders, which are used at Stennis Space Center. The original software could be activated by a command- line interface only; the present software offers the option of a command-line or graphical user interface. The present software also offers the option of batch-file operation (activation by a file that contains command lines for operations performed consecutively). The present software is also more reliable than was the original software: The original software was plagued by several deficiencies that made it difficult to execute, modify, and test. In addition, when using the original software to extract data that had been recorded within specified intervals of time, the resolution with which one could control starting and stopping times was no finer than about a second (or, in some cases, several seconds). In contrast, the present software is capable of controlling playback times to within 1/100 second of times specified by the user, assuming that the tape-recorder clock is accurate to within 1/100 second.

Cheng, Chiu-Fu↗
NASA NTRS2006

Steps Towards the Standardization of a More Efficient Uplink Protocol and Code

In June 2004, NASA announced a new vision for the further exploration of the Moon and Mars. The vision includes a long-term human and robotic program to explore the solar system, starting with a return to the Moon that will ultimately enable future exploration of Mars and other destinations. Inherent in this endeavor is the need to transfer the communication technology developed for lunar missions to deep space whenever possible. Furthermore, greater data throughput on the uplink will be required for future nominal operations for the Exploration missions given their highly interactive nature and the need to send files in both directions. Therefore, it is prudent for standards bodies i.e., CCSDS to develop the underlying communication recommendations necessary to deliver greater data throughput to meet future agencies' needs.

link layer↗
NASA NTRS1993

Computer program for analysis of high speed, single row, angular contact, spherical roller bearing, SASHBEAN. Volume 1: User's guide

The computer program SASHBEAN (Sikorsky Aircraft Spherical Roller High Speed Bearing Analysis) analyzes and predicts the operating characteristics of a Single Row, Angular Contact, Spherical Roller Bearing (SRACSRB). The program runs on an IBM or IBM compatible personal computer, and for a given set of input data analyzes the bearing design for it's ring deflections (axial and radial), roller deflections, contact areas and stresses, induced axial thrust, rolling element and cage rotation speeds, lubrication parameters, fatigue lives, and amount of heat generated in the bearing. The dynamic loading of rollers due to centrifugal forces and gyroscopic moments, which becomes quite significant at high speeds, is fully considered in this analysis. For a known application and it's parameters, the program is also capable of performing steady-state and time-transient thermal analyses of the bearing system. The steady-state analysis capability allows the user to estimate the expected steady-state temperature map in and around the bearing under normal operating conditions. On the other hand, the transient analysis feature provides the user a means to simulate the 'lost lubricant' condition and predict a time-temperature history of various critical points in the system. The bearing's 'time-to-failure' estimate may also be made from this (transient) analysis by considering the bearing as failed when a certain temperature limit is reached in the bearing components. The program is fully interactive and allows the user to get started and access most of its features with a minimal of training. For the most part, the program is menu driven, and adequate help messages were provided to guide a new user through various menu options and data input screens. All input data, both for mechanical and thermal analyses, are read through graphical input screens, thereby eliminating any need of a separate text editor/word processor to edit/create data files. Provision is also available to select and view the contents of output files on the monitor screen if no paper printouts are required. A separate volume (Volume-2) of this documentation describes, in detail, the underlying mathematical formulations, assumptions, and solution algorithms of this program.

Aggarwal, Arun K.↗
NASA NTRS2005

Integration of Launch Vehicle Simulation/Analysis Tools and Lunar Cargo Lander Design

Simulation and analysis of vehicle performance is essential for design of a new launch vehicle system. It is more and more demand to have an integrated, highly efficient, robust simulation tool with graphical user interface (GUI) for vehicle performance and simulations. The objectives of this project are to integrate and develop launch vehicle simulation and analysis tools in MATLAB/Simulink under PC Platform, to develop a vehicle capable of being launched on a Delta-IV Heavy Launch Vehicle which can land on the moon with the goal of pre-implanting cargo for a new lunar mission, also with the capability of selecting other launch vehicles that are capable of inserting a payload into Trans-Lunar Injection (TLI). The vehicle flight simulation software, MAVERIC-II (Marshall Aerospace VEhicle Representation In 'C'), developed by Marshall Space Flight Center was selected as a starting point for integration of simulation/analysis tools. The goals are to convert MAVERIC-II from UNIX to PC platform and build input/output GUI s in the MATLAB environment, and then integrate them under MATLAB/Simulink with other modules. Currently, MAVERIC-II has been successfully converted from UNIX to PC using Microsoft Services for UNIX subsystem on PC. Input/Output GUI's have been done for some key input/output files. Calling MAVERIC-II from Simulink has been tested. Details regarding Lunar Cargo Lander Design are described in Part 2/2 of the paper on page X-1.

Shiue, Yeu-Sheng Paul↗
NASA NTRS2000

BOREAS HYD-1 Under-Canopy Precipitation Data

Under-canopy precipitation measurements were made by the BOREAS HYD-1 science team in 1994, 1995, and 1996 at various flux tower sites in the NSA and SSA. In 1994, these data were collected at the NSA-OJP, NSA-YJP, SSA-OJP, and SSA-YJP sites. Starting in 1995 and ending in 1997, data were collected at the NSA-OBS, NSA-OJP, NSA-YJP, and SSA-OA. These data were collected to support HYD-01 research by measuring the amount of water that falls through the canopy and is intercepted by the ground or moss. These data coincide with volumetric soil moisture measurements made by HYD-01. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Cuenca, Richard H.↗
NASA NTRS2000

BOREAS RSS-14 Level-1a GOES-8 Visible, IR and Water Vapor Images

The BOREAS RSS-14 team collected and processed several GOES-7 and GOES-8 image data sets that covered the BOREAS study region. The level-1a GOES-8 images were created by BORIS personnel from the level-1 images delivered by FSU personnel. The data cover 14-Jul-1995 to 21-Sep-1995 and 12-Feb-1996 to 03-Oct-1996. The data start out as three bands with 8-bit pixel values and end up as five bands with 10-bit pixel values. No major problems with the data have been identified. The differences between the level-1 and level-1a GOES-8 data are the formatting and packaging of the data. The images missing from the temporal series of level-1 GOES-8 images were zero-filled by BORIS staff to create files consistent in size and format. In addition, BORIS staff packaged all the images of a given type from a given day into a single file, removed the header information from the individual level-1 files, and placed it into a single descriptive ASCII header file. The data are contained in binary image format files. Due to the large size of the images, the level-1a GOES-8 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1a GOES-8 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS2013

Multi-User Space Link Extension (SLE) System

The Multi-User Space (MUS) Link Extension system, a software and data system, provides Space Link Extension (SLE) users with three space data transfer services in timely, complete, and offline modes as applicable according to standards defined by the Consultative Committee for Space Data Systems (CCSDS). MUS radically reduces the schedule, cost, and risk of implementing a new SLE user system, minimizes operating costs with a lights-out approach to SLE, and is designed to require no sustaining engineering expense during its lifetime unless changes in the CCSDS SLE standards, combined with new provider implementations, force changes. No software modification to MUS needs to be made to support a new mission. Any systems engineer with Linux experience can begin testing SLE user service instances with MUS starting from a personal computer (PC) within five days. For flight operators, MUS provides a familiar-looking Web page for entering SLE configuration data received from SLE. Operators can also use the Web page to back up a space mission's entire set of up to approximately 500 SLE service instances in less than five seconds, or to restore or transfer from another system the same amount of data from a MUS backup file in about the same amount of time. Missions operate each MUS SLE service instance independently by sending it MUS directives, which are legible, plain ASCII strings. MUS directives are usually (but not necessarily) sent through a TCP-IP (Transmission Control Protocol Internet Protocol) socket from a MOC (Mission Operations Center) or POCC (Payload Operations Control Center) system, under scripted control, during "lights-out" spacecraft operation. MUS permits the flight operations team to configure independently each of its data interfaces; not only commands and telemetry, but also MUS status messages to the MOC. Interfaces can use single- or multiple-client TCP/IP server sockets, TCP/IP client sockets, temporary disk files, the system log, or standard in, standard out, or standard error as applicable. By defining MUS templates in ASCII, the flight operations team can include any MUS system variable in telemetry or command headers or footers, and/or in status messages. Data fields can be arranged within messages in different sequences, according to the mission s needs. The only constraints imposed are on the format of MUS directive strings, and some bare minimum logical requirements that must be met in order for MUS to read the mission control center's spacecraft command inputs. The MUS system imposes no limits or constraints on the numbers and combinations of missions and SLE service instances that it will support simultaneously. At any time, flight operators may add, change, delete, bind, connect, or disconnect.

Perkins, Toby↗
NASA NTRS2014

External Dependencies-Driven Architecture Discovery and Analysis of Implemented Systems

A method for architecture discovery and analysis of implemented systems (AIS) is disclosed. The premise of the method is that architecture decisions are inspired and influenced by the external entities that the software system makes use of. Examples of such external entities are COTS components, frameworks, and ultimately even the programming language itself and its libraries. Traces of these architecture decisions can thus be found in the implemented software and is manifested in the way software systems use such external entities. While this fact is often ignored in contemporary reverse engineering methods, the AIS method actively leverages and makes use of the dependencies to external entities as a starting point for the architecture discovery. The AIS method is demonstrated using the NASA's Space Network Access System (SNAS). The results show that, with abundant evidence, the method offers reusable and repeatable guidelines for discovering the architecture and locating potential risks (e.g. low testability, decreased performance) that are hidden deep in the implementation. The analysis is conducted by using external dependencies to identify, classify and review a minimal set of key source code files. Given the benefits of analyzing external dependencies as a way to discover architectures, it is argued that external dependencies deserve to be treated as first-class citizens during reverse engineering. The current structure of a knowledge base of external entities and analysis questions with strategies for getting answers is also discussed.

Ganesan, Dharmalingam↗
NASA NTRS2009

Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery

This work extends the lossless data compression technique described in Fast Lossless Compression of Multispectral- Image Data, (NPO-42517) NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26. The original technique was extended to include a near-lossless compression option, allowing substantially smaller compressed file sizes when a small amount of distortion can be tolerated. Near-lossless compression is obtained by including a quantization step prior to encoding of prediction residuals. The original technique uses lossless predictive compression and is designed for use on multispectral imagery. A lossless predictive data compression algorithm compresses a digitized signal one sample at a time as follows: First, a sample value is predicted from previously encoded samples. The difference between the actual sample value and the prediction is called the prediction residual. The prediction residual is encoded into the compressed file. The decompressor can form the same predicted sample and can decode the prediction residual from the compressed file, and so can reconstruct the original sample. A lossless predictive compression algorithm can generally be converted to a near-lossless compression algorithm by quantizing the prediction residuals prior to encoding them. In this case, since the reconstructed sample values will not be identical to the original sample values, the encoder must determine the values that will be reconstructed and use these values for predicting later sample values. The technique described here uses this method, starting with the original technique, to allow near-lossless compression. The extension to allow near-lossless compression adds the ability to achieve much more compression when small amounts of distortion are tolerable, while retaining the low complexity and good overall compression effectiveness of the original algorithm.

Xie, Hua↗
NASA NTRS2009

EOS MLS Level 1B Data Processing, Version 2.2

A computer program performs level- 1B processing (the term 1B is explained below) of data from observations of the limb of the Earth by the Earth Observing System (EOS) Microwave Limb Sounder (MLS), which is an instrument aboard the Aura spacecraft. This software accepts, as input, the raw EOS MLS scientific and engineering data and the Aura spacecraft ephemeris and attitude data. Its output consists of calibrated instrument radiances and associated engineering and diagnostic data. [This software is one of several computer programs, denoted product generation executives (PGEs), for processing EOS MLS data. Starting from level 0 (representing the aforementioned raw data, the PGEs and their data products are denoted by alphanumeric labels (e.g., 1B and 2) that signify the successive stages of processing.] At the time of this reporting, this software is at version 2.2 and incorporates improvements over a prior version that make the code more robust, improve calibration, provide more diagnostic outputs, improve the interface with the Level 2 PGE, and effect a 15-percent reduction in file sizes by use of data compression.

Perun, Vincent↗
NASA NTRS2017

Battery Data MI Importer Template Quick Start Guide

In order to ensure the persistent availability and reliability of test data generated over the course of the project, the M-SHELLS Project has decided to store acquired test data, as well as associated pedigree information, in the Granta Materials Intelligence (MI) database. To facilitate that effort, an importer template and associated graphical user interface (GUI) software have been developed, with this guide providing the operating instructions for their use. The template and automation software GUI are contained in the BatteryDataImporter.xlsm Excel workbook, and are to be used to import M-SHELLS summary, or pedigree, data and the associated raw test data results into an importer template-based file, formatted in such a way as to be ready for immediate upload to the Test Data: Battery Performance table of the Granta MI database. The provided GUI enables the user to select the appropriate summary data file(s), with each file containing the required information to identify any associated raw test data file(s) to be processed. In addition to describing the setup and operation of the importer template and GUI software, this guide also provides instructions for uploading processed data to the database and for viewing the data following upload.

Levinson, Laurie H.↗
NASA NTRS2010

Using MERRA Gridded Innovations for Quantifying Uncertainties in Analysis Fields and Diagnosing Observing System Inhomogeneities

MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context. The characterization of uncertainty in reanalysis fields is a commonly requested feature by users of such data. While intercomparison with reference data sets is common practice for ascertaining the realism of the datasets, such studies typically are restricted to long term climatological statistics and seldom provide state dependent measures of the uncertainties involved. In principle, variational data assimilation algorithms have the ability of producing error estimates for the analysis variables (typically surface pressure, winds, temperature, moisture and ozone) consistent with the assumed background and observation error statistics. However, these "perceived error estimates" are expensive to obtain and are limited by the somewhat simplistic errors assumed in the algorithm. The observation minus forecast residuals (innovations) by-product of any assimilation system constitutes a powerful tool for estimating the systematic and random errors in the analysis fields. Unfortunately, such data is usually not readily available with reanalysis products, often requiring the tedious decoding of large datasets and not so-user friendly file formats. With MERRA we have introduced a gridded version of the observations/innovations used in the assimilation process, using the same grid and data formats as the regular datasets. Such dataset empowers the user with the ability of conveniently performing observing system related analysis and error estimates. The scope of this dataset will be briefly described. We will present a systematic analysis of MERRA innovation time series for the conventional observing system, including maximum-likelihood estimates of background and observation errors, as well as global bias estimates. Starting with the joint PDF of innovations and analysis increments at observation locations we propose a technique for diagnosing bias among the observing systems, and document how these contextual biases have evolved during the satellite era covered by MERRA.

da Silva, Arlindo↗
NASA NTRSDate not supplied

New Ways of Facilitating Improved Data Discovery and Access for NASA's Suborbital Earth Science Observations

NASA conducts field research in various Earth Science disciplines utilizing airborne and other non-satellite platforms to acquire in situ and remotely sensed observations indicative of physical processes across a range of scales. Field efforts are key in the development and validation of instruments and satellite algorithm refinements. The heterogeneous data, with a range of file formats, scales, and acquisition methods, support research in several science areas. NASA’s archive process assigns data products to discipline-oriented Distributed Active Archive Centers (DAACs) for stewardship. Over time, individual DAACs have developed tools for data browsing and serving disparate user bases. As science becomes more interdisciplinary, researchers need to incorporate observations from multiple campaigns, and multiple DAACs, into their work. Motivated in part by this shifting paradigm of needs, the Catalog of Archived Suborbital Earth Science Investigations (CASEI) was created. CASEI provides a single starting point to browse, search, and discover airborne and field data. Contextual metadata are organized and inter-linked allowing intuitive, integrated exploration across all NASA DAACs. Campaign science objectives, platform and instrument configurations, geographical details, geophysical concepts, and more are tracked in CASEI’s database, facilitating multi-parameter search, browse, and discovery of relevant data products. Researchers are able to directly access associated data products, via DOI links, regardless of the DAAC where they reside. Significant events, key time periods of high science interest within the longer-duration campaign effort, are also indicated and allow for a more efficient identification of critical data subsets. This presentation describes CASEI’s development, intensive metadata curation process, and demonstrates the web interface experience. Initial content metrics and plans for continued maintenance will also be discussed.

metadata↗
NASA NTRS2013

Calculating and Mitigating the Risk of a Cut Glove to a Space Walking Astronaut

One of the high risk operations on the International Space Station (ISS) is conducting a space walk, or an Extra Vehicular Activity (EVA). Threats to the space walking crew include airlock failures, space suit failures, and strikes from micro ]meteoroids and orbital debris (MM/OD). There are risks of becoming untethered from the space station, being pinched between the robotic arm and a piece of equipment, tearing your suit on a sharp edge, and other human errors that can be catastrophic. For decades NASA identified and tried to control sharp edges on external structure and equipment by design; however a new and unexpected source of sharp edges has since become apparent. Until recently, one of the underappreciated environmental risks was damage to EVA gloves during a spacewalk. The ISS has some elements which have been flying in the environment of space for over 14 years. It has and continues to be bombarded with MM/OD strikes that have created small, sharp craters all over the structure, including the dedicated EVA handrails and surrounding structure. These craters are capable of cutting through several layers of the EVA gloves. Starting in 2006, five EVA crewmembers reported cuts in their gloves so large they rendered the gloves unusable and in some cases cut the spacewalk short for the safety of the crew. This new hazard took engineers and managers by surprise. NASA has set out to mitigate this risk to safety and operations by redesigning the spacesuit gloves to be more resilient and designing a clamp to isolate MM/OD strikes on handrails, and is considering the necessity of an additional tool to repair strikes on non ]handrail surfaces (such as a file). This paper will address how the ISS Risk Team quantified an estimate of the MM/OD damage to the ISS, and the resulting likelihood of sustaining a cut glove in order to measure the effectiveness of the solutions being investigated to mitigate this risk to the mission and crew.

Castillo, Theresa↗
NASA NTRS2004

Computing and combustion

Coming into the Combustion Branch of the Turbomachinery and Propulsion Systems Division, there was not any set project planned out for me to work on. This was understandable, considering I am only at my sophmore year in college. Also, my mentor was a division chief and it was expected that I would be passed down the line. It took about a week for me to be placed with somebody who could use me. My first project was to write a macro for TecPlot. Commonly, a person would have a 3D contour volume modeling something such as a combustion engine. This 3D volume needed to have slices extracted from it and made into 2D scientific plots with all of the appropriate axis and titles. This was very tedious to do by hand. My macro needed to automate the process. There was some education I needed before I could start, however. First, TecPlot ran on Unix and Linux, like a growing majority of scientific applications. I knew a little about Linux, but I would need to know more to use the software at hand. I took two classes at the Learning Center on Unix and am now comfortable with Linux and Unix. I already had taken Computer Science I and II, and had undergone the transformation from Computer Programmer to Procedural Epistemologist. I knew how to design efficient algorithms, I just needed to learn the macro language. After a little less than a week, I had learned the basics of the language. Like most languages, the best way to learn more of it was by using it. It was decided that it was best that I do the macro in layers, starting simple and adding features as I went. The macro started out slicing with respect to only one axis, and did not make 2D plots out of the slices. Instead, it lined them up inside the solid. Next, I allowed for more than one axis and placed each slice in a separate frame. After this, I added code that transformed each individual slice-frame into a scientific plot. I also made frames for composite volumes, which showed all of the slices in the same XYZ space. I then designed an addition companion macro that exported each frame into its own image file. I then distributed the macros to a test group, and am awaiting feedback. In the meantime, a am researching the possible applications of distributed computing on the National Combustor Code. Many of our Linux boxes were idle for most of the day. The department thinks that it would be wonderful if we could get all of these idle processors to work on a problem under the NCC code. The client software would have to be easily distributed, such as in screensaver format or as a program that only ran when the computer was not in use. This project proves to be an interesting challenge.

Thompson, Daniel↗